Triple
T12642712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gooniyandi people |
E301937
|
entity |
| Predicate | haveConnectionToLand |
P99675
|
FINISHED |
| Object | ancestral lands in central Kimberley |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: ancestral lands in central Kimberley | Statement: [Gooniyandi people, haveConnectionToLand, ancestral lands in central Kimberley]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveConnectionToLand Context triple: [Gooniyandi people, haveConnectionToLand, ancestral lands in central Kimberley]
-
A.
hasConnectionToLand
chosen
Indicates that one entity is linked, attached, or otherwise related to a specific piece or area of land.
-
B.
isInLand
Indicates that one entity is located within the geographical boundaries of a land area or territory of another entity.
-
C.
hasLandComponent
Indicates that something includes, consists of, or is associated with a land-based part or portion as one of its components.
-
D.
usesOnLand
Indicates that one entity employs or operates another entity specifically in a land-based context.
-
E.
hasLandCutOffBy
Indicates that one land area is separated or interrupted from another by an intervening feature or boundary.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960b47130819097e1162ed4fc993a |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:17 p.m.